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J Pediatr ; 127(4): 571-7, 1995 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-7562278

RESUMO

OBJECTIVES: The validity of equations for the calculation of resting metabolic rate (RMR) were studied and new predictive equations were developed. STUDY DESIGN: The RMR was measured in a sample of 371 10- to 16-year-old prepubertal and postpubertal children. The study group included 193 male (116 nonobese and 77 obese) and 178 female (119 nonobese and 59 obese) subjects; for each group the RMRs predicted from five equations recommended for this age group were compared. The RMR was assessed by indirect calorimetry with a ventilated hood system for 45 minutes after an overnight fast. Body composition was estimated from skin-fold measurements. RESULTS: The mean +/- SD RMR was found to be 5600 +/- 972 kJ/24 hr and 7223 +/- 1220 kJ/24 hr in nonobese and obese boys, and 5112 +/- 632 kJ/24 hr and 6665 +/- 1106 kJ/24 hr in nonobese and obese girls, respectively. All five equations applicable to 10- to 16-year-old children overestimated RMR by 7.5% to 18.1% (p < 0.001 for each equation). Stepwise regression analysis, with independent variables such as age, weight, height, and gender, allowed development of new predictive equations for the calculation of RMR in 10- to 16-year-old boys (RMR = 50.9 Weight (kg) + 25.3 Height (cm) -50.3 Age (yr) + 26.9; R2 = 0.884, p < 0.0001) and girls (RMR = 51.2 Weight (kg) + 24.5 Height (cm) - 207.5 Age (yr) + 1629.8; R2 = 0.824, p < 0.0001). These predictive equations were tested in a second, independent cohort of children (80 male and 61 female subject) and were found to give a reliable estimate of RMR in 10- to 16-year-old obese and nonobese adolescents. CONCLUSIONS: The currently used predictive equations overestimate RMR in 10- to 16-year-old children. The use of the newly developed equations is recommended.


Assuntos
Obesidade/metabolismo , Adolescente , Antropometria , Índice de Massa Corporal , Calorimetria , Criança , Estudos de Coortes , Metabolismo Energético , Feminino , Humanos , Masculino , Estudos Prospectivos , Análise de Regressão , Dobras Cutâneas
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